Bayesian Analysis is a statistical method that applies Bayes' Theorem to update the probability of a hypothesis as more evidence or information becomes available. It combines prior knowledge, represented as a prior probability, with new data to produce a revised probability, known as the posterior probability. This approach allows for a more flexible interpretation of uncertainty in various fields, including medicine, finance, and machine learning. In Bayesian Analysis, the process begins with an initial belief about a situation, which is then adjusted as new data is collected. This iterative updating process helps researchers and analysts make informed decisions based on both existing knowledge and new evidence, enhancing the accuracy of predictions and conclusions.